- Designing and implementing production-grade APIs and backend services in Python

- Building and maintaining LLM-powered systems, including agent frameworks and orchestration using tools like LangChain and LangGraph

- Efficiently integrating LLM calls into backend workflows

- Collaborating across functions to develop reliable, maintainable systems

Requirements :

- 5+ years of experience as a backend or full-stack engineer with a strong backend focus

- Advanced proficiency in Python

- Practical experience integrating LLMs (e.g., RAG pipelines, agent frameworks, LangChain, LangGraph, or similar)

- Background in machine learning engineering is a strong plus

- Solid understanding of service architecture and production deployment workflows

- Minimum 5 years in backend/full-stack development with strong Python & LLM integration experience

- Hands-on LLM integration in production (not academic/chatbot-only experience)

- Expertise in designing production-grade APIs and backend services

- Practical experience with LangChain, LangGraph, RAG pipelines, agent frameworks

- Strong knowledge of async workflows, deployment, observability, and performance

- This is a software engineering role (not data science, analytics, or annotation)